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Anna Nagy (133)

B01 CH12.pdf

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Anna Nagy

Chapter 12Understanding research results description and correlationStats are used for describing data and making inferences on sample data Scales of Measurement areviewLevels of a variable can be decribed by 4 scales o Nominal no numerical quantitative properties o Ordinal rank order o Interval quantitative properties no absolute 0o Ratio quantitative properties has an absolute 0 Analyzing the results if research investigationDepending on the way the variables are studied there are 3 basic ways of describing the results o Comparing group percentages o Correlating scores of individuals on two variables o Comparing group means Comparing group percentagesExample studying if which females or males like traveling more o Lets say out of 50 females and 50 males 80 of females like to travel60 of males like to travel o Need to focus onbecause of variable of liking travel or disliking travel is nominal Correlating individual scoresUsed when you do not have distinct subject groupsIndividuals are measured on 2 variables o Each variable has a range of numerical valuesExample do people who sit near the front receive higher grades Comparing group meansExample studying effect of exposure to an aggressive adult on childrens play o On average how many aggressive acts did the children perform during play in both groupsAggression is a ratio scale variable because there is a true zero and equal intervals Frequency distributionsWhen analyzing results it is useful to start by making a frequency distribution of the dataFrequency Distribution indicates the number of individuals that receive each possible score on a variable o Useful to look at this in terms of sExample how many students in a class received a specific score on an exam Graphing frequency Distributions
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